Big Data and manufacturing priorities

Building data alignment for complex decision making in manufacturing

An important aspect of the manufacturing executive’s job is to illustrate the connection between operations and corporate strategy, prioritise investments, and identify how to best measure progress and milestones.

It starts with the alignment between operational and financial metrics but it typically requires examining vast amounts of data to identify the key criteria supporting the operational behaviours that significantly impact profits.

In other words, operations must identify the purpose and focus of performance management. If the goal is savings, they focus on cutting cost.

If the goal is growth and market share, the focus shifts to customer satisfaction and revenue-generating activities. If the goal is to ensure performance, the focus is placed on quality and productivity.

And if the goal is corporate social responsibility, the emphasis is placed on ensuring product safety and quality of life.

Related:

We’ve seen a significant push in the market towards Big Data and analytics. These tools provide better ways to identify the operational inefficiencies that have the greatest impact on the company’s ability to meet objectives.

Figure 1, based on data from the Aberdeen Group research report Manufacturing Operations Management and Lean, shows how Best-in-Class manufacturing executives understand that aligning performance management with corporate priorities leaves room to be more proactive and able to find new ways to solve problems.

The figures compare the Best-in-Class (defined as the top fifth of the respondents based on margin, new product introduction success rate and completed-on-time deliveries) to All Others (bottom 80 per cent).

Best-in-Class companies are more likely to run business process experiments, try new BI technologies and invest in automated dashboards and analytics to empower employees with incentives and accountability to improve the way that they work.

Once operational goals are understood, the next step is to define the data approach that best supports their ability to execute and measure.

We have been hearing for years how CIOs and senior IT professionals need to bury the hatchet with line of business managers and, instead of focusing on the latest bleeding-edge technology for its own sake, seek to better understand the overall strategic objectives of their organisations.